Dedicated GPU memory guides
These Windows/NVIDIA guide pages use dedicated GPU memory as the primary fit budget and keep partial offload separate from a full GPU fit.
Meta · Llama
Review available GGUF variants, quantization choices, and conservative memory-planning levels for running Llama 3.2 3Blocally.
| Variant | Quantization | Estimated file | Minimum load | Planning memory |
|---|---|---|---|---|
| Llama 3.2 3B · Q4_K_M | Q4_K_M | 1.7 GB | 2.7 GB | 3.7 GB |
| Llama 3.2 3B · Q8_0 | Q8_0 | 3.2 GB | 4.2 GB | 5.2 GB |
GPU compatibility
These pages compare this model's recorded GGUF variants against the dedicated VRAM of selected NVIDIA GPUs. They are deterministic memory-fit checks, not performance benchmarks.
These Windows/NVIDIA guide pages use dedicated GPU memory as the primary fit budget and keep partial offload separate from a full GPU fit.
Apple Silicon pages use conservative unified-memory budgets and Metal-capable local inference terminology instead of treating the Mac as a CUDA workstation.
These are deterministic memory-planning checks, not benchmark claims. Context length, runtime settings, offload behavior, and concurrent apps can change practical fit.